COMPUTER SYSTEM FOR MULTI-SOURCE DOMAIN ADAPTATIVE TRAINING BASED ON SINGLE NEURAL NETWORK WITHOUT OVERFITTING AND METHOD THEREOF
Abstract:
Various embodiments relate to a computer system for multi-source domain adaptative training based on a single neural network without overfitting and a method thereof. The various embodiments may configured to regularize data sets of a plurality of domains, extract information shared between the regularized data sets, and implement a training model by performing training based on the extracted information.
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